Methods and Apparatus to Determine Audience Engagement

This disclosure is a continuation of U.S. Patent Application No. 17/974,492, titled “METHODS AND APPARATUS TO DETERMINE AUDIENCE ENGAGEMENT,” and filed on Oct. 26, 2022, which is hereby incorporated by reference in its entirety.

This disclosure relates generally to audience measurement and, more particularly, to methods and apparatus to determine audience engagement.

Audience measurement entities (AMEs) monitor user interaction with media devices, such as smartphones, tablets, laptops, smart televisions, etc. To facilitate such monitoring, AMEs enlist panelists and install meters at the media presentation locations of those panelists. The meters monitor media presentations and transmit media monitoring information to a central facility of the AME. Such media monitoring information enables the AMEs to, among other things, monitor exposure to advertisements, determine advertisement effectiveness, determine user behavior, identify purchasing behavior associated with various demographics, etc.

Audience measurement entities (AMEs) (also referred to herein as "ratings entities" or “monitoring companies”) determine demographic reach for advertising and media programming based on registered panel members. That is, an audience measurement entity enrolls people that consent to being monitored into a panel. During enrollment, the audience measurement entity receives demographic information from the enrolling people so that subsequent correlations may be made between advertisement/media exposure to those panelists and different demographic markets. For example, AMEs desire knowledge on how users interact with media devices, such as smartphones, tablets, laptops, smart televisions, etc. In particular, AMEs monitor media presentations made at the media devices to, among other things, monitor exposure to advertisements, determine advertisement effectiveness, determine user behavior, identify purchasing behavior associated with various demographics, etc.

As used herein, the term "media" includes any type of content and/or advertisement delivered via any type of distribution medium. Thus, media includes television programming or advertisements, radio programming or advertisements, movies, web sites, streaming media, etc.

In addition to determining demographic reach for advertising and media programming based on registered panel members, audience measurement entities attempt to determine a viewer’s engagement, focus, and/or attention to media exposure. To determine a viewer’s attention to a media exposure, some example audience measurement entities employ one or more facial recognition cameras that determine if an audience member is actively viewing a media presentation device. However, such systems can be costly, demanding hardware such as cameras and IR lighting to capture a panelist’s face and video processing software to determine if the panelist is looking at the screen. Furthermore, such systems may require privacy waivers from panelists.

Many media monitoring techniques are limited to determining exposure to TV programming without providing engagement metrics. Furthermore, such techniques often demand active participation by a panelist who indicates they are present by using a remote control to log in to a meter device. In such systems, an AME cannot determine if the panelist is actively engaged in the program they are exposed to.

As used herein, source audio may include electrical signals (e.g., analog and/or digital signals) that represent sound from a media source. As used herein, ambient noise may include any sound in an environment associated with a media presentation. Ambient noise may include sounds generated by panelists, viewers, media presentations, digital devices, speakers, pets, the environment (e.g., raindrops, wind, etc.). In some examples, ambient noise includes signals (e.g., audio signals, etc.) in a media presentation environment or household that are related to the media signals.

In examples disclosed herein, an area associated with the media presentation may include any area in which a panelist is capable of being exposed to the media. For example, a media presentation may be provided on a television in a living room of a panelist household. In such an example, the area associated with the media presentation may be the living room. However, in such an example, the area associated with the media presentation may extend beyond the living room (e.g., to an adjoining kitchen, through an open doorway, etc.). Thus, the boundaries of the area associated with the media exposure are based in part on the panelist’s ability to be exposed to the media.

Example metering devices disclosed herein detect or measure panelist engagement, focus, and/or attention to media exposure(s). The example metering devices can be used with or without cameras and/or other facial recognition techniques for measuring user engagement. To detect or determine a panelist’s attention to media exposure, example metering devices and related methods disclosed herein obtain source audio of a media presentation, obtain ambient noise in an area associated with the media presentation, determine an intensity of a difference between the source audio and the ambient noise, and determine an engagement level of an audience of the media presentation based on a duration the intensity satisfies a threshold value. Example methods may determine if a panelist is engaged or is distracted during a media presentation (e.g., based on an attention/distraction scale). For example, metering devices disclosed herein can detect ambient noise during media presentations that can be evaluated or analyzed to determine a panelist’s attention or distraction during the media exposure.

Examples disclosed herein recognize that although media may be detected on a media device, the presentation of the media does not necessarily indicate that an audience is paying attention to (e.g., is engaged with) the media presentation. Examples disclosed herein generate engagement information (e.g., a degree of engagement, a likelihood of engagement, etc.) indicative of whether or not an audience member (e.g., a panelist member) is paying attention to a media presentation.

Examples disclosed herein may use metrics collected by a portable device to correlate the panelist's engagement with the ambient sound in the environment. For example, the portable device can be a portable/wearable meter (e.g., the portable people meter (PPM) of The Nielsen Company (US), LLC), a media meter in a media device (e.g., a TV), a smartphone, a smart speaker, etc. In examples disclosed herein, the portable device may include a microphone to collect ambient sound, which is used to determine audience engagement.

1 FIG. 1 FIG. 100 104 116 is an example systemto determine audience engagement. In the illustrated example of, a householdhas been statistically selected to develop media (e.g., television) ratings data for a population/demographic of interest. People become panelists via, for example, a user interface presented on a media device (e.g., via a media device, via a website, etc.). People become panelists in additional or alternative manners such as, for example, via a telephone interview, by completing an online survey, etc. Additionally or alternatively, people may be contacted and/or enlisted using any desired methodology (e.g., random selection, statistical selection, phone solicitations, Internet advertisements, surveys, advertisements in shopping malls, product packaging, etc.). In some examples, an entire family may be enrolled as a household of panelists.

106 108 110 104 In the illustrated example, a first panelist, a second panelist, and a third panelistof the householdhave registered with an audience measurement entity (e.g., by agreeing to be a panelist) and have provided their demographic information to the audience measurement entity as part of a registration process to enable associating demographics with media exposure activities (e.g., television exposure, radio exposure, Internet exposure, etc.). The demographic data includes, for example, age, gender, income level, educational level, marital status, geographic location, race, etc., of a panelist.

1 FIG. 104 130 130 104 130 In the illustrated example of, the householdincludes an example media presentation environment. The example media presentation environmentis a living room in the household. However, the example media presentation environmentcan additionally or alternatively be any other type(s) of environment(s) such as, for example, a theater, a restaurant, a tavern, a retail location, an arena, etc.

1 FIG. 116 116 116 116 106 108 110 In the illustrated example of, the example media deviceis a television. However, the example media devicecan correspond to any type of audio, video, and/or multimedia presentation device capable of presenting media audibly and/or visually. In some examples, the media device(e.g., a television) may communicate audio to another media presentation device (e.g., an audio/video receiver) for output by one or more speakers (e.g., surround sound speakers, a sound bar, etc.). As another example, the media devicecan correspond to a multimedia computer system, a personal digital assistant, a cellular/mobile smartphone, a radio, a home theater system, stored audio and/or video played back from a memory such as a digital video recorder or a digital versatile disc, a webpage, and/or any other communication device capable of presenting media to an audience (e.g., the panelists,, and).

132 132 132 1 FIG. A media sourceis shown in the illustrated example of. The media sourceis a satellite dish. However, in some examples the media sourcemay be any means to provide media from media provider(s), such as, but not limited to, a cable media service provider, a radio frequency (RF) media provider, an Internet based provider (e.g., IPTV), a satellite media service provider, etc. The media may be radio media, television media, pay per view media, movies, Internet Protocol Television (IPTV), satellite television (TV), Internet radio, satellite radio, digital television, digital radio, stored media (e.g., a compact disk (CD), a Digital Versatile Disk (DVD), a Blu-ray disk, etc.), any other type(s) of broadcast, multicast and/or unicast medium, audio and/or video media presented (e.g., streamed) via the Internet, a video game, targeted broadcast, satellite broadcast, video on demand, etc.

116 132 116 116 116 116 132 1 FIG. The example media deviceof the illustrated example shown inis a device that receives media from the media sourcefor presentation. In some examples, the media deviceis capable of directly presenting media (e.g., via a display) while, in other examples, the media devicepresents the media on separate media presentation equipment (e.g., speakers, a display, etc.). Thus, as used herein, “media devices” may or may not be able to present media without assistance from a second device. Media devices are typically consumer electronics. For example, the media deviceof the illustrated example could be a personal computer such as a laptop computer, and, thus, capable of directly presenting media (e.g., via an integrated and/or connected display and speakers). In some examples, the media devicecan correspond to a television and/or display device that supports the National Television Standards Committee (NTSC) standard, the Phase Alternating Line (PAL) standard, the Système Électronique pour Couleur avec Mémoire (SECAM) standard, a standard developed by the Advanced Television Systems Committee (ATSC), such as high definition television (HDTV), a standard developed by the Digital Video Broadcasting (DVB) Project, etc. Advertising, such as an advertisement and/or a preview of other programming that is or will be offered by the media source, etc., is also typically included in the media. While a television is shown in the illustrated example, any other type(s) and/or number(s) of media device(s) may additionally or alternatively be used. For example, Internet-enabled mobile handsets (e.g., a smartphone, an iPod®, etc.), video game consoles (e.g., Xbox®, PlayStation 3, etc.), tablet computers (e.g., an iPad®, a Motorola™ Xoom™, etc.), digital media players (e.g., a Roku® media player, a Slingbox®, a Tivo®, etc.), smart televisions, desktop computers, laptop computers, servers, etc. may additionally or alternatively be used.

118 116 116 116 118 116 116 In the illustrated example, a media device metercan be physically coupled to the media deviceor may be configured to capture signals emitted externally by the media device(e.g., free field audio) such that direct physical coupling to the media deviceis not required. For example, the media device meterof the illustrated example may employ non-invasive monitoring not involving any physical connection to the media device(e.g., via Bluetooth® connection, WIFI® connection, acoustic watermarking, etc.) and/or invasive monitoring involving one or more physical connections to the media device(e.g., via USB connection, a High Definition Media Interface (HDMI) connection, an Ethernet cable connection, etc.).

118 102 128 126 102 102 102 The example media device meterdetects exposure to media and electronically stores monitoring information (e.g., a code/watermark detected with the presented media, a signature of the presented media, an identifier of a panelist present at the time of the presentation, a timestamp of the time of the presentation) of the presented media. The stored monitoring information is then transmitted back to the AME central facilityvia a network. In some examples, the stored monitoring information is transmitted to example data storage circuitryincluded in the AME central facilityfor processing the monitoring information. In some examples, ambient noise data is not transmitted to the AME central facility, while source audio data is transmitted to the AME central facility.

116 118 In examples disclosed herein, to monitor media presented by the media device, the media device meterof the illustrated example employs audio watermarking techniques and/or signature based-metering techniques. Audio watermarking is a technique used to identify media, such as television broadcasts, radio broadcasts, advertisements (television and/or radio), downloaded media, streaming media, prepackaged media, etc. Existing audio watermarking techniques identify media by embedding one or more audio codes (e.g., one or more watermarks), such as media identifying information and/or an identifier that may be mapped to media identifying information, into an audio and/or video component of the media. In some examples, the audio or video component is selected to have a signal characteristic sufficient to hide the watermark. As used herein, the terms “code” and “watermark” are used interchangeably and are defined to mean any identification information (e.g., an identifier) that may be inserted or embedded in the audio or video of media (e.g., a program or advertisement) for the purpose of identifying the media or for another purpose such as tuning (e.g., a packet identifying header). As used herein “media” refers to audio and/or visual (still or moving) content and/or advertisements. To identify watermarked media, the watermark(s) are extracted and used to access a table of reference watermarks that are mapped to media identifying information.

Unlike media monitoring techniques based on codes and/or watermarks included with and/or embedded in the monitored media, fingerprint or signature-based media monitoring techniques generally use one or more inherent characteristics of the monitored media during a monitoring time interval to generate a substantially unique proxy for the media. Such a proxy is referred to as a signature or fingerprint, and can take any form (e.g., a series of digital values, a waveform, etc.) representative of any aspect(s) of the media signal(s) (e.g., the audio and/or video signals forming the media presentation being monitored). A signature may be a series of signatures collected in series over a timer interval. A good signature is repeatable when processing the same media presentation, but is unique relative to other (e.g., different) presentations of other (e.g., different) media. Accordingly, the term “fingerprint” and “signature” are used interchangeably herein and are defined herein to mean a proxy for identifying media that is generated from one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g., generating and/or collecting) signature(s) representative of a media signal (e.g., an audio signal and/or a video signal) output by a monitored media device and comparing the monitored signature(s) to one or more references signatures corresponding to known (e.g., reference) media sources. Various comparison criteria, such as a cross-correlation value, a Hamming distance, etc., can be evaluated to determine whether a monitored signature matches a particular reference signature. When a match between the monitored signature and one of the reference signatures is found, the monitored media can be identified as corresponding to the particular reference media represented by the reference signature that with matched the monitored signature. Because attributes, such as an identifier of the media, a presentation time, a broadcast channel, etc., are collected for the reference signature, these attributes may then be associated with the monitored media whose monitored signature matched the reference signature.

118 116 118 116 116 116 118 120 134 118 116 118 116 For example, the media device meterof the illustrated example senses audio (e.g., acoustic signals or ambient audio) output (e.g., emitted) by the media device. For example, the media device meterprocesses the signals obtained from the media deviceto detect media and/or source identifying signals (e.g., audio watermarks) embedded in portion(s) (e.g., audio portions) of the media presented by the media device. To sense ambient audio output by the media device, the media device meterof the illustrated example includes a first audio sensor(e.g., a first microphone) and a second audio sensor(e.g., a second microphone). In some examples, the media device metermay process audio signals obtained from the media devicevia a direct cable connection to detect media and/or source identifying audio watermarks embedded in such audio signals. In some examples, the media device metermay process audio signals to generate respective audio signatures from the media presented by the media device.

118 118 106 108 110 118 130 118 116 To generate exposure data for the media, identification(s) of media to which the audience is exposed are correlated with people data (e.g., presence information) collected by the media device meter. The media device meterof the illustrated example collects inputs (e.g., audience monitoring data) representative of the identities of the audience member(s) (e.g., the panelists,, and). In some examples, the media device metercollects audience monitoring data by periodically or non-periodically prompting audience members in the monitored media presentation environmentto identify themselves as present in the audience (e.g., audience identification information). In some examples, the media device meterresponds to events (e.g., the media deviceis turned on, a channel change, detection of an infrared control signal, etc.) by prompting the audience member(s) to self-identify.

118 120 120 130 116 130 118 120 In some examples, the media device meteris positioned in a location such that the first audio sensor(e.g., the first microphone) receives ambient audio produced by the television and/or other devices of the media presentation environmentwith sufficient quality to identify media presented by the media deviceand/or other devices of the media presentation environment(e.g., a surround sound speaker system). For example, in examples disclosed herein, the media device meterand a first audio sensor (e.g., the first microphone) may be placed on top of a television, secured to a bottom portion of a television, etc.

1 FIG. 134 130 112 114 112 114 106 108 110 112 114 130 112 114 116 106 108 110 112 114 106 108 110 112 114 118 120 134 In the illustrated example of, the example second microphonedetects ambient sound in the media presentation environment. In some examples, the meter(s)and/orare portable people meter(s) (PPM(s)) of The Nielsen Company (US), LLC, wearable meter(s), smartphone(s), etc. In some examples, the meter(s),are associated with panelist(s) (e.g., the panelists,, and). The example meter(s),include an audio sensor (e.g., a microphone) to collect ambient audio data from the media presentation environment. In some examples, the meter(s),collect ambient sound that includes sound generated by the media device(e.g., the television) and sound generated by the panelist(s),, and/or. In some examples, the meter(s),determine engagement information for associated panelist(s) (e.g., the panelists,, and) based on the ambient audio data collected by the meter(s),, the media device meter, and/or the first and second microphonesand.

128 128 The networkof the illustrated example is a wide area network (WAN) such as the Internet. However, in some examples, local networks may additionally or alternatively be used. Moreover, the example networkmay be implemented using any type of public or private network, such as, but not limited to, the Internet, a telephone network, a local area network (LAN), a cable network, and/or a wireless network, or any combination thereof.

102 124 102 118 112 114 102 102 The AME central facilityof the illustrated example is implemented by one or more AME servers. The AME central facilityprocesses and stores data received from the media device meterand the meters,. Additionally or alternatively, the AME central facilitycan be implemented via a cloud service (e.g., AWS®, etc.). In this example, the AME central facilitycan further store and process generated watermark and signature reference data.

124 118 124 124 124 124 112 114 118 122 122 118 124 122 104 102 104 102 104 118 102 124 1 FIG. 2 FIG. 3 6 FIGS.- 2 FIG. 3 6 FIGS.- The example AME serverprocesses the collected media identifying information and/or data received by the media device meterto detect, identify, credit, etc., respective media assets and/or portions thereof (e.g., media segments) associated with the corresponding data. For example, the AME serverdetermines signature matches between the monitored signatures and reference signatures and credits the media assets associated with the media identifying information of the monitored signatures. For example, the AME servercan compare the media identifying information to generated reference data to determine what respective media is associated with the corresponding media identifying information. The AME serverof the illustrated example also analyzes the media identifying information to determine if the media asset(s), and/or particular portion(s) (e.g., segment(s)) thereof, associated with the signature match and/or watermark match is (are) to be credited. In some examples, the AME serveralso collects engagement information/data from the example meters,to associate with the media exposure data identified by the media device meter. The example engagement analysis circuitrymay credit media exposure to an identified media asset and also determines engagement information for that media exposure (e.g., was the panelist actually engaged/paying attention to the media during the media exposure). In the illustrated example of, the example engagement analysis circuitryis shown in both the example media device meterand the example AME server. Thus, operations of the engagement analysis circuitrymay be performed in the household, the AME central facility, and/or both the householdand the AME central facility. In some examples, one or more of the processes described in relation toand/ormay be performed in the household(e.g., performed by the media device meter) and one or more of the processes described in relation toand/ormay be performed in the audience measurement entity central facility(e.g., performed by the AME server).

2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 122 122 122 is a block diagram of engagement analysis circuitryto determine audience engagement with a media presentation. The engagement analysis circuitryofmay be instantiated (e.g., creating an instance of, bring into being for any length of time, materialize, implement, etc.) by processor circuitry such as a central processing unit executing instructions. Additionally or alternatively, the engagement analysis circuitryofmay be instantiated (e.g., creating an instance of, bring into being for any length of time, materialize, implement, etc.) by an ASIC or an FPGA structured to perform operations corresponding to the instructions. It should be understood that some or all of the circuitry ofmay, thus, be instantiated at the same or different times. Some or all of the circuitry may be instantiated, for example, in one or more threads executing concurrently on hardware and/or in series on hardware. Moreover, in some examples, some or all of the circuitry ofmay be implemented by one or more virtual machines and/or containers executing on the microprocessor.

122 202 116 202 134 1 FIG. 1 FIG. The engagement analysis circuitryincludes ambient noise measurement circuitry. Ambient noise may include any sound in an environment, whether or not the sound is associated with a media presentation. For example, ambient noise may include both audio from a media presentation and noise generated by panelists (e.g., panelists talking, panelists watching media not associated with the media presentation deviceof, etc.). The ambient noise measurement circuitryobtains audio from a front facing microphone (e.g., the second microphoneof).

202 202 208 206 202 The example ambient noise measurement circuitrymay measure an intensity of an ambient noise sample. For example, the ambient noise measurement circuitrymay measure ambient noise in decibels and provide the measurement to rules engine circuity, and/or comparator circuitryfor further analysis. In some examples, the ambient noise measurement circuitrymay measure ambient sound at regular intervals (e.g., sample every 10 seconds, sample every 100 seconds, sample every 1000 seconds, etc.).

202 202 112 114 202 212 214 1 FIG. In some examples, the ambient noise measurement circuitrymay measure sound in an environment (e.g., a room) with a front-facing microphone or microphone array. In some examples, the ambient noise measurement circuitrymay obtain audio from a meter device (e.g., the meter devices,of). The ambient noise measurement circuitrymay also provide measurements of ambient audio to data storage circuitryvia a bus.

202 202 712 202 800 304 404 504 202 900 202 202 7 FIG. 8 FIG. 3 FIG. 4 FIG. 5 FIG. 9 FIG. In some examples, the apparatus includes means for measuring ambient noise in an environment associated with a media presentation. For example, the means for measuring may be implemented by ambient noise measurement circuity. In some examples, the ambient noise measurement circuitymay be instantiated by processor circuitry such as the example processor circuitryof. For instance, the ambient noise measurement circuitymay be instantiated by the example general purpose processor circuitryofexecuting machine executable instructions such as that implemented by at least blocksof,of, andof. In some examples ambient noise measurement circuitymay be instantiated by hardware logic circuitry, which may be implemented by an ASIC or the FPGA circuitryofstructured to perform operations corresponding to the machine readable instructions. Additionally or alternatively, the ambient noise measurement circuitymay be instantiated by any other combination of hardware, software, and/or firmware. For example, the ambient noise measurement circuitymay be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an Application Specific Integrated Circuit (ASIC), a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to execute some or all of the machine readable instructions and/or to perform some or all of the operations corresponding to the machine readable instructions without executing software or firmware, but other structures are likewise appropriate.

122 204 204 204 116 204 120 116 202 1 FIG. 1 FIG. 1 FIG. The example engagement analysis circuitryincludes source audio measurement circuitry. The example source audio measurement circuitrymeasures media audio that is presented to an audience. The source audio measurement circuitrymay perform a direct monitoring of audio of a media presentation. For example, direct monitoring of the audio of the media presentation may be performed by tapping an audio output on a media presentation device (e.g., the media deviceof). In other examples, the source audio measurement circuitrymay obtain the source audio based on a microphone (e.g., the first microphoneof) that is directed to a media device speaker (e.g., the media deviceof). In such an example, by placing a microphone proximate to and facing a speaker of a media presentation device, the example source audio measurement circuitrymay obtain a direct measurement of the source audio with less ambient noise.

204 204 208 The example source audio measurement circuitrymay also obtain information about a media presentation that includes the source audio. For example, the source audio measurement circuitrymay obtain information related to playback of the media (e.g., fast-forward, skip, pause), a genre of the media (e.g., sporting event, comedy, drama, etc.). Such information may be provided to the rules engine circuitryto classify sound from the audience.

204 204 712 204 800 302 404 504 204 900 204 204 7 FIG. 8 FIG. 3 FIG. 4 FIG. 5 FIG. 9 FIG. In some examples, the apparatus includes means for measuring source audio in an environment associated with a media presentation. For example, the second means for measuring may be implemented by source audio measurement circuitry. In some examples, the source audio measurement circuitrymay be instantiated by processor circuitry such as the example processor circuitryof. For instance, the source audio measurement circuitrymay be instantiated by the example general purpose processor circuitryofexecuting machine executable instructions such as that implemented by at least blocksof,of, andof. In some examples the source audio measurement circuitrymay be instantiated by hardware logic circuitry, which may be implemented by an ASIC or the FPGA circuitryofstructured to perform operations corresponding to the machine readable instructions. Additionally or alternatively, the source audio measurement circuitrymay be instantiated by any other combination of hardware, software, and/or firmware. For example, the source audio measurement circuitrymay be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an Application Specific Integrated Circuit (ASIC), a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to execute some or all of the machine readable instructions and/or to perform some or all of the operations corresponding to the machine readable instructions without executing software or firmware, but other structures are likewise appropriate.

122 206 206 202 204 206 206 206 208 The example engagement analysis circuitryincludes example comparator circuitry. The example comparator circuitrycompares ambient noise provided by the ambient noise measurement circuitryand source audio provided by the source audio measurement circuitry. The comparator circuitry may determine an intensity (e.g., a value in decibels) of a difference between ambient noise in an environment and a source audio measurement. The comparator circuitrymay also determine a period of time (e.g., a length of time) the intensity satisfies a threshold value. For example, the comparator circuitrymay determine a period of time the intensity is greater than a first threshold value. The comparator circuitrymay also determine a second period of time the intensity is less than a second threshold value. Then, based on the first and second determinations, the comparator circuitry may identify temporary fluctuations in intensity and provide this information to rules engine circuitryfor classification of the audience sound.

206 206 206 208 The comparator circuitrymay determine one or more portions of the ambient noise that correspond to the source audio. After the identification, the comparator circuitrymay determine a remaining portion of the source audio is associated with an audience (e.g., an audience sound). The comparator circuitrymay then determine the audience sound is associated with a panelist and/or is not associated with a panelist. The identification may be performed by providing the audience sound and any other identifying information (e.g., metadata related to audience/panelists, metadata related to media that is presented, etc.) to the rules engine circuitry.

206 206 712 206 800 306 406 410 506 510 206 900 206 206 7 FIG. 8 FIG. 3 FIG. 4 FIG. 5 FIG. 9 FIG. In some examples, the apparatus includes means for comparing ambient noise to source audio. For example, the means for comparing may be implemented by the comparator circuitry. In some examples, the comparator circuitrymay be instantiated by processor circuitry such as the example processor circuitryof. For instance, the comparator circuitrymay be instantiated by the example general purpose processor circuitryofexecuting machine executable instructions such as that implemented by at least blocksof,-of, and-of. In some examples comparator circuitrymay be instantiated by hardware logic circuitry, which may be implemented by an ASIC or the FPGA circuitryofstructured to perform operations corresponding to the machine readable instructions. Additionally or alternatively, the comparator circuitrymay be instantiated by any other combination of hardware, software, and/or firmware. For example, the comparator circuitrymay be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an Application Specific Integrated Circuit (ASIC), a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to execute some or all of the machine readable instructions and/or to perform some or all of the operations corresponding to the machine readable instructions without executing software or firmware, but other structures are likewise appropriate.

122 208 208 206 202 204 208 208 208 208 124 1 FIG. The example engagement analysis circuitryincludes the rules engine circuitry. The rules engine circuitryobtains information from the comparator circuitryregarding any differences (e.g., intensity of difference, duration of difference, etc.) between ambient noise and source audio of a media presentation. Based on the difference and any additional information provided by the ambient noise measurement circuitryand/or the source audio measurement circuitry(e.g., audience metrics, genre of source audio, tuning information, media control, etc.), the rules engine circuitrydetermines audience engagement. In some examples, the rules engine circuitryassigns an engagement classification to the media presentation that indicates how engaged the audience of the media is. For example, the rules engine circuitrymay categorize an audience engagement (e.g., categorize as low engagement, medium engagement, high engagement) based on a rules engine (e.g., a series of rules to categorize engagement). The rules engine circuitrymay then generate a code (e.g., a code for engagement data categorizing the engagement) to pair with crediting information for a presenter of the media presentation. Such information may be transmitted to an AME (e.g., the AME serverof). In some examples, all source audio and ambient noise data is maintained within the presentation environment (e.g., the home) to provide enhanced panelist privacy.

208 206 202 204 208 4 FIG. The rules engine circuitrymay make an engagement classification based on, for example, rules that are pre-determined (e.g., based on experimentation and/or heuristics). In some examples, the rules may be included in a classification tree that evaluates input data provided by the comparator circuitry, the ambient noise measurement circuitry, and/or the source audio measurement circuitryaccording to a series of rules. An example of using the rules engine circuitrydetermining audience engagement is shown in.

For example, a first rule may be that a difference in sound intensity (e.g., volume, decibel level, signal strength) between an ambient noise and a source audio that is less than a threshold value indicates an audience is engaged. A second rule may be that if the difference in sound intensity is greater than a threshold value, the audience is not engaged. These rules may be based on an observation that if an audience is not engaged in a media presentation, they may begin talking or performing another activity. Such activities increases ambient noise in the room without altering the source audio.

Thus, if a difference between source audio and ambient noise in an environment exceeds a threshold, the audience may be categorized as distracted and/or not engaged with the media presentation. Engagement may further be categorized as low, medium, or high based on, for example, the intensity of the difference between ambient noise and source audio. The categorization may also be based on duration elevated ambient noise and/or a classification of a type of ambient noise. In some examples, engagement is assigned a continuous value (e.g., an engagement metric, an engagement rating) that is inversely proportional to audience noise and/or room noise (e.g., based on a difference between source audio and ambient noise).

122 122 Another rule may determine engagement based on characteristics of source audio and/or a media presentation. For example, sporting events may be associated with rules that account for an excited (e.g., active, relatively loud) audience. In another example, an audience engaged with a drama may be relatively silent, generating relatively less ambient noise. Yet, in such a scenario, the audience of the drama may be similarly engaged with the media as the audience of the sporting event. Therefore, the engagement analysis circuitrymay generate improved engagement metrics by analyzing characteristics (e.g., media genre(s)) of the source audio. Furthermore, in some examples, the engagement analysis circuitrymay determine engagement based on an expected duration of ambient noise associated with a media playback. For example, an audience engaged with a horror movie may generate short, intense bursts of ambient noise. In some examples, an engagement confidence value can be determined that increases in response to combination of a classification and an additional audience behavior, such as a channel change or control of the media presentation (e.g., play media, pause media, fast-forward media, slow media, etc.).

208 Another rule may determine that, in response to a difference between source audio and ambient noise being less than a threshold value, the audience is either highly engaged, asleep, or involved in a quiet activity. Further rules may be used to identify which of these categories most accurately represents the audience engagement. For example, if the audience is involved in a quiet activity, such as browsing an app on a phone, there may still be short bursts of uncorrelated noise from the phone as the panelist scrolls through the app. Another rule may identify certain types of ambient noise as pet noise. For example, animal sounds like dogs barking can be identified based on the rules engine circuitry. Another rule may identify that when a panelist is farther away from a microphone (e.g., panelist is in a large media presentation environment), the expected intensity of ambient noise generated by the panelist is relatively less. Therefore, a rule may adjust an engagement value and/or engagement categorization based on a distance of a panelist and/or audience from the microphone.

208 In some examples, the rules engine circuitrymay include a rule that alters a classification based on a panelist being identified as present based on activity of a meter device. Furthermore, any of the above rules may be modified based on changes in the source audio and/or changes to the environment caused by the audience (e.g., an audio volume change or a channel change).

208 122 208 206 208 208 212 In some examples, the rules engine circuitry(e.g., and/or more generally, the engagement analysis circuitry) may include neural network circuitry to classify ambient noise, generate audience measurement classifications, and/or modify audience measurement classifications. For example, neural network circuitry of the rules engine circuitrymay implement a convolutional neural network that includes various convolutional layers, max pooling layers, fixed embedding layers, global averaging layers, etc. In some examples, the example neural network circuitry may include additional and/or alternative machine learning models to predict a class label for input ambient noise, source audio, source audio metadata, and/or output of the comparator circuitry. For example, the rules engine circuitrymay interoperate with other classification algorithms (e.g., logistic regression, naive bayes, k-nearest neighbors, decision tree, support vector machine) to provide improved classification results for audience engagement. The example rules engine circuitrymay also include neural network training circuitry and/or retrieve training data from the example data storage circuitry, which can be used to train an engagement classifier. In some examples, the neural network circuitry may perform pre-processing on the training data and/or deduplicate elements of the training set before training.

208 208 712 208 800 306 402 408 416 506 512 602 606 208 900 202 202 7 FIG. 8 FIG. 3 FIG. 4 FIG. 5 FIG. 6 FIG. 9 FIG. In some examples, the apparatus includes means for determining audience engagement based on rules and/or a machine learning classifier. For example, the means for determining may be implemented by rules engine circuitry. In some examples, the rules engine circuitrymay be instantiated by processor circuitry such as the example processor circuitryof. For instance, the rules engine circuitrymay be instantiated by the example general purpose processor circuitryofexecuting machine executable instructions such as that implemented by at least blocksof,and-of,-of, and/or-of. In some examples the rules engine circuitrymay be instantiated by hardware logic circuitry, which may be implemented by an ASIC or the FPGA circuitryofstructured to perform operations corresponding to the machine readable instructions. Additionally or alternatively, the ambient noise measurement circuitymay be instantiated by any other combination of hardware, software, and/or firmware. For example, the ambient noise measurement circuitymay be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an Application Specific Integrated Circuit (ASIC), a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to execute some or all of the machine readable instructions and/or to perform some or all of the operations corresponding to the machine readable instructions without executing software or firmware, but other structures are likewise appropriate.

122 202 204 206 208 212 122 202 204 206 208 212 122 122 1 FIG. 2 FIG. 2 FIG. 1 FIG. 1 FIG. 1 FIG. 2 FIG. While an example manner of implementing the engagement analysis circuitryofis illustrated in, one or more of the elements, processes, and/or devices illustrated inmay be combined, divided, re-arranged, omitted, eliminated, and/or implemented in any other way. Further, the example ambient noise measurement circuitry, the example source audio measurement circuitry, the example comparator circuitry, the example rules engine circuitry, the example data storage circuitry, and/or more generally the example engagement analysis circuitryof, may be implemented by hardware alone or by hardware in combination with software and/or firmware. Thus, for example, any of the example ambient noise measurement circuitry, the example source audio measurement circuitry, the example comparator circuitry, the example rules engine circuitry, the example data storage circuitry, and/or more generally the example engagement analysis circuitryof, could be implemented by processor circuitry, analog circuit(s), digital circuit(s), logic circuit(s), programmable processor(s), programmable microcontroller(s), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)), and/or field programmable logic device(s) (FPLD(s)) such as Field Programmable Gate Arrays (FPGAs). Further still, the example engagement analysis circuitryofmay include one or more elements, processes, and/or devices in addition to, or instead of, those illustrated in, and/or may include more than one of any or all of the illustrated elements, processes and devices.

122 712 700 800 900 122 3 6 FIGS.- 7 FIG. 8 9 FIGS.and/or 3 FIG. Flowcharts representative of example hardware logic circuitry, machine readable instructions, hardware implemented state machines, and/or any combination thereof for implementing the engagement analysis circuitryis shown in. The machine readable instructions may be one or more executable programs or portion(s) of an executable program for execution by processor circuitry, such as the processor circuitryshown in the example processor platformdiscussed below in connection withand/or the example processor circuitry discussed below in connection with(e.g., the microprocessorand/or the FPGA circuitry. The program may be embodied in software stored on one or more non-transitory computer readable storage media such as a compact disk (CD), a floppy disk, a hard disk drive (HDD), a solid-state drive (SSD), a digital versatile disk (DVD), a Blu-ray disk, a volatile memory (e.g., Random Access Memory (RAM) of any type, etc.), or a non-volatile memory (e.g., electrically erasable programmable read-only memory (EEPROM), FLASH memory, an HDD, an SSD, etc.) associated with processor circuitry located in one or more hardware devices, but the entire program and/or parts thereof could alternatively be executed by one or more hardware devices other than the processor circuitry and/or embodied in firmware or dedicated hardware. The machine readable instructions may be distributed across multiple hardware devices and/or executed by two or more hardware devices (e.g., a server and a client hardware device). For example, the client hardware device may be implemented by an endpoint client hardware device (e.g., a hardware device associated with a user) or an intermediate client hardware device (e.g., a radio access network (RAN)) gateway that may facilitate communication between a server and an endpoint client hardware device). Similarly, the non-transitory computer readable storage media may include one or more mediums located in one or more hardware devices. Further, although the example program is described with reference to the flowchart illustrated in, many other methods of implementing the example engagement analysis circuitrymay alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined. Additionally or alternatively, any or all of the blocks may be implemented by one or more hardware circuits (e.g., processor circuitry, discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to perform the corresponding operation without executing software or firmware. The processor circuitry may be distributed in different network locations and/or local to one or more hardware devices (e.g., a single-core processor (e.g., a single core central processor unit (CPU)), a multi-core processor (e.g., a multi-core CPU), etc.) in a single machine, multiple processors distributed across multiple servers of a server rack, multiple processors distributed across one or more server racks, a CPU and/or a FPGA located in the same package (e.g., the same integrated circuit (IC) package or in two or more separate housings, etc.).

The machine readable instructions described herein may be stored in one or more of a compressed format, an encrypted format, a fragmented format, a compiled format, an executable format, a packaged format, etc. Machine readable instructions as described herein may be stored as data or a data structure (e.g., as portions of instructions, code, representations of code, etc.) that may be utilized to create, manufacture, and/or produce machine executable instructions. For example, the machine readable instructions may be fragmented and stored on one or more storage devices and/or computing devices (e.g., servers) located at the same or different locations of a network or collection of networks (e.g., in the cloud, in edge devices, etc.). The machine readable instructions may require one or more of installation, modification, adaptation, updating, combining, supplementing, configuring, decryption, decompression, unpacking, distribution, reassignment, compilation, etc., in order to make them directly readable, interpretable, and/or executable by a computing device and/or other machine. For example, the machine readable instructions may be stored in multiple parts, which are individually compressed, encrypted, and/or stored on separate computing devices, wherein the parts when decrypted, decompressed, and/or combined form a set of machine executable instructions that implement one or more operations that may together form a program such as that described herein.

In another example, the machine readable instructions may be stored in a state in which they may be read by processor circuitry, but require addition of a library (e.g., a dynamic link library (DLL)), a software development kit (SDK), an application programming interface (API), etc., in order to execute the machine readable instructions on a particular computing device or other device. In another example, the machine readable instructions may need to be configured (e.g., settings stored, data input, network addresses recorded, etc.) before the machine readable instructions and/or the corresponding program(s) can be executed in whole or in part. Thus, machine readable media, as used herein, may include machine readable instructions and/or program(s) regardless of the particular format or state of the machine readable instructions and/or program(s) when stored or otherwise at rest or in transit.

The machine readable instructions described herein can be represented by any past, present, or future instruction language, scripting language, programming language, etc. For example, the machine readable instructions may be represented using any of the following languages: C, C++, Java, C#, Perl, Python, JavaScript, HyperText Markup Language (HTML), Structured Query Language (SQL), Swift, etc.

3 6 FIGS.- As mentioned above, the example operations ofmay be implemented using executable instructions (e.g., computer and/or machine readable instructions) stored on one or more non-transitory computer and/or machine readable media such as optical storage devices, magnetic storage devices, an HDD, a flash memory, a read-only memory (ROM), a CD, a DVD, a cache, a RAM of any type, a register, and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the terms non-transitory computer readable medium and non-transitory computer readable storage medium are expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are used herein to be open ended terms. Thus, whenever a claim employs any form of “include” or “comprise” (e.g., comprises, includes, comprising, including, having, etc.) as a preamble or within a claim recitation of any kind, it is to be understood that additional elements, terms, etc., may be present without falling outside the scope of the corresponding claim or recitation. As used herein, when the phrase “at least” is used as the transition term in, for example, a preamble of a claim, it is open-ended in the same manner as the term “comprising” and “including” are open ended. The term “and/or” when used, for example, in a form such as A, B, and/or C refers to any combination or subset of A, B, C such as (1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) B with C, or (7) A with B and with C. As used herein in the context of describing structures, components, items, objects and/or things, the phrase “at least one of A and B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing structures, components, items, objects and/or things, the phrase “at least one of A or B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. As used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase “at least one of A and B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase “at least one of A or B” is intended to refer to implementations including any of (1) at least one A, (2) at least one B, or (3) at least one A and at least one B.

As used herein, singular references (e.g., “a”, “an”, “first”, “second”, etc.) do not exclude a plurality. The term “a” or “an” object, as used herein, refers to one or more of that object. The terms “a” (or “an”), “one or more”, and “at least one” are used interchangeably herein. Furthermore, although individually listed, a plurality of means, elements or method actions may be implemented by, e.g., the same entity or object. Additionally, although individual features may be included in different examples or claims, these may possibly be combined, and the inclusion in different examples or claims does not imply that a combination of features is not feasible and/or advantageous.

3 FIG. 2 FIG. 3 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 300 300 302 204 304 202 306 206 208 308 122 is a flowchart representative of example machine readable instructions and/or example operationsthat may be executed and/or instantiated by processor circuitry to implement the engagement analysis circuitry ofto determine audience engagement. The machine readable instructions and/or the operationsofbegin at block, at which the source audience measurement circuitryofobtains source audio of a media presentation. At block, the example ambient measurement circuitryofobtains ambient noise of an area associated with the media presentation. Next, at block, the example comparator circuitryofand/or the example rules engine circuitryofdetermines audience engagement based on a difference between ambient noise and source audio. Finally, at block, the example engagement analysis circuitryoftransmits engagement data to an AME server. The instructions end.

4 FIG. 2 FIG. 4 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 400 208 400 402 122 404 202 204 414 208 is a flowchart representative of example machine readable instructions and/or example operationsthat may be executed and/or instantiated by processor circuitry to implement the rules engine circuitryof. The machine readable instructions and/or the operationsofbegin at block, at which the example engagement analysis circuitryofdetermines if a panelist and/or audience is logged in to a meter device. If so, the instructions continue at blockat which the example ambient noise measurement circuitryofand/or the example source audio measurement circuitryofobtain source audio and ambient noise. Otherwise, control continues at block, at which the rules engine circuitryofdetermines the audience is not engaged.

406 206 408 208 410 208 416 208 2 FIG. 2 FIG. 2 FIG. 2 FIG. At block, the example comparator circuitryofidentifies a difference between source audio and ambient noise. Then, at block, the example rules engine circuitryofdetermines if an intensity of the difference is greater than a threshold value. If so, control continues at blockat which the example rules engine circuitryofidentifies a duration the intensity exceeds the threshold value. Otherwise, the instructions continue at blockat which the example rules engine circuitryofdetermines the audience is engaged.

412 208 414 208 416 208 2 FIG. 2 FIG. 2 FIG. At block, the example rules engine circuitryofdetermines if the duration is greater than threshold value. If so, the instructions continue at blockat which the rules engine circuitryofdetermines the audience is not engaged. Otherwise, control continues at blockat which the example rules engine circuitryofdetermines an audience is engaged. The instructions end.

5 FIG. 2 FIG. 5 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 500 122 500 502 122 504 202 204 506 208 508 208 510 208 512 208 is a flowchart representative of example machine readable instructions and/or example operationsthat may be executed and/or instantiated by processor circuitry to implement the engagement analysis circuitryofto modify an audience engagement classification. The machine readable instructions and/or the operationsofbegin at block, at which the example engagement analysis circuitryofdetermines if a meter device is active. At block, the ambient noise measurement circuitryofand/or the source audio measurement circuitryofobtain source audio and ambient noise. At block, the example rules engine circuitryofdetermines audience engagement based on first comparison of source audio to ambient sound. At block, the rules engine circuitryofdetermines audience engagement based on second comparison of source audio to ambient sound. At block, the rules engine circuitryofidentifies a change in engagement based on a difference between the first and second determinations. At block, the rules engine circuitryofmodifies an engagement classification based on a source audio volume change or a channel change. The instructions end.

6 FIG. 2 FIG. 6 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 2 FIG. 600 122 600 602 204 604 202 204 206 208 606 208 is a flowchart representative of example machine readable instructions and/or example operationsthat may be executed and/or instantiated by processor circuitry to implement the engagement analysis circuitryofto classify audience engagement based on a machine learning classification. The machine readable instructions and/or the operationsofbegin at block, at which the source audio measurement circuitryofdetermines identifying characteristics of source audio. At block, the example ambient noise measurement circuitryof, the example source audio measurement circuitryof, and/or the example comparator circuitryofprovide ambient noise, source audio, and source audio identifying characteristics to the rules engine circuitryof. At block, the example rules engine circuitryofclassifies audience engagement based on output of neural network circuitry. The instructions end.

7 FIG. 3 6 FIGS.- 2 FIG. 700 122 700 TM is a block diagram of an example processor platformstructured to execute and/or instantiate the machine readable instructions and/or the operations ofto implement the engagement analysis circuitryof. The processor platformcan be, for example, a server, a personal computer, a workstation, a self-learning machine (e.g., a neural network), a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPad), a personal digital assistant (PDA), an Internet appliance, a DVD player, a CD player, a digital video recorder, a Blu-ray player, a gaming console, a personal video recorder, a set top box, a headset (e.g., an augmented reality (AR) headset, a virtual reality (VR) headset, etc.) or other wearable device, or any other type of computing device.

700 712 712 712 712 712 202 204 206 208 212 The processor platformof the illustrated example includes processor circuitry. The processor circuitryof the illustrated example is hardware. For example, the processor circuitrycan be implemented by one or more integrated circuits, logic circuits, FPGAs, microprocessors, CPUs, GPUs, DSPs, and/or microcontrollers from any desired family or manufacturer. The processor circuitrymay be implemented by one or more semiconductor based (e.g., silicon based) devices. In this example, the processor circuitryimplements ambient noise measurement circuitry, the example source audio measurement circuitry, the example comparator circuitry, the example rules engine circuitry, and/or the example data storage circuitry.

712 713 712 714 716 718 714 716 714 716 717 The processor circuitryof the illustrated example includes a local memory(e.g., a cache, registers, etc.). The processor circuitryof the illustrated example is in communication with a main memory including a volatile memoryand a non-volatile memoryby a bus. The volatile memorymay be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory (RDRAM®), and/or any other type of RAM device. The non-volatile memorymay be implemented by flash memory and/or any other desired type of memory device. Access to the main memory,of the illustrated example is controlled by a memory controller.

700 720 720 The processor platformof the illustrated example also includes interface circuitry. The interface circuitrymay be implemented by hardware in accordance with any type of interface standard, such as an Ethernet interface, a universal serial bus (USB) interface, a Bluetooth® interface, a near field communication (NFC) interface, a Peripheral Component Interconnect (PCI) interface, and/or a Peripheral Component Interconnect Express (PCIe) interface.

722 720 722 712 722 In the illustrated example, one or more input devicesare connected to the interface circuitry. The input device(s)permit(s) a user to enter data and/or commands into the processor circuitry. The input device(s)can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a track-pad, a trackball, an isopoint device, and/or a voice recognition system.

724 720 724 720 One or more output devicesare also connected to the interface circuitryof the illustrated example. The output device(s)can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display (LCD), a cathode ray tube (CRT) display, an in-place switching (IPS) display, a touchscreen, etc.), a tactile output device, a printer, and/or speaker. The interface circuitryof the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip, and/or graphics processor circuitry such as a GPU.

720 726 The interface circuitryof the illustrated example also includes a communication device such as a transmitter, a receiver, a transceiver, a modem, a residential gateway, a wireless access point, and/or a network interface to facilitate exchange of data with external machines (e.g., computing devices of any kind) by a network. The communication can be by, for example, an Ethernet connection, a digital subscriber line (DSL) connection, a telephone line connection, a coaxial cable system, a satellite system, a line-of-site wireless system, a cellular telephone system, an optical connection, etc.

700 728 728 The processor platformof the illustrated example also includes one or more mass storage devicesto store software and/or data. Examples of such mass storage devicesinclude magnetic storage devices, optical storage devices, floppy disk drives, HDDs, CDs, Blu-ray disk drives, redundant array of independent disks (RAID) systems, solid state storage devices such as flash memory devices and/or SSDs, and DVD drives.

732 728 714 716 3 6 FIGS.- The machine executable instructions, which may be implemented by the machine readable instructions of, may be stored in the mass storage device, in the volatile memory, in the non-volatile memory, and/or on a removable non-transitory computer readable storage medium such as a CD or DVD.

8 FIG. 7 FIG. 7 FIG. 3 6 FIG.- 2 FIG. 8 FIG. 3 6 FIGS.- 712 712 800 800 800 800 802 800 802 800 802 802 802 is a block diagram of an example implementation of the processor circuitryof. In this example, the processor circuitryofis implemented by a general purpose microprocessor. The general purpose microprocessor circuitryexecutes some or all of the machine readable instructions of the flowcharts ofto effectively instantiate the circuitry ofas logic circuits to perform the operations corresponding to those machine readable instructions. In some such examples, the circuitry ofis instantiated by the hardware circuits of the microprocessorin combination with the instructions. For example, the microprocessormay implement multi-core hardware circuitry such as a CPU, a DSP, a GPU, an XPU, etc. Although it may include any number of example cores(e.g., 1 core), the microprocessorof this example is a multi-core semiconductor device including N cores. The coresof the microprocessormay operate independently or may cooperate to execute machine readable instructions. For example, machine code corresponding to a firmware program, an embedded software program, or a software program may be executed by one of the coresor may be executed by multiple ones of the coresat the same or different times. In some examples, the machine code corresponding to the firmware program, the embedded software program, or the software program is split into threads and executed in parallel by two or more of the cores. The software program may correspond to a portion or all of the machine readable instructions and/or operations represented by the flowchart of.

802 804 804 802 804 804 802 806 802 806 802 820 1 1 1 800 810 2 810 820 802 810 714 716 7 FIG. The coresmay communicate by a first example bus. In some examples, the first busmay implement a communication bus to effectuate communication associated with one(s) of the cores. For example, the first busmay implement at least one of an Inter-Integrated Circuit (I2C) bus, a Serial Peripheral Interface (SPI) bus, a PCI bus, or a PCIe bus. Additionally or alternatively, the first busmay implement any other type of computing or electrical bus. The coresmay obtain data, instructions, and/or signals from one or more external devices by example interface circuitry. The coresmay output data, instructions, and/or signals to the one or more external devices by the interface circuitry. Although the coresof this example include example local memory(e.g., Level 1 (L) cache that may be split into an Ldata cache and an Linstruction cache), the microprocessoralso includes example shared memorythat may be shared by the cores (e.g., Level 2 (L_ cache)) for high-speed access to data and/or instructions. Data and/or instructions may be transferred (e.g., shared) by writing to and/or reading from the shared memory. The local memoryof each of the coresand the shared memorymay be part of a hierarchy of storage devices including multiple levels of cache memory and the main memory (e.g., the main memory,of). Typically, higher levels of memory in the hierarchy exhibit lower access time and have smaller storage capacity than lower levels of memory. Changes in the various levels of the cache hierarchy are managed (e.g., coordinated) by a cache coherency policy.

802 802 814 816 818 1 820 822 802 814 802 816 802 816 816 816 816 818 816 802 818 818 818 802 822 8 FIG. Each coremay be referred to as a CPU, DSP, GPU, etc., or any other type of hardware circuitry. Each coreincludes control unit circuitry, arithmetic and logic (AL) circuitry (sometimes referred to as an ALU), a plurality of registers, the Lcache, and a second example bus. Other structures may be present. For example, each coremay include vector unit circuitry, single instruction multiple data (SIMD) unit circuitry, load/store unit (LSU) circuitry, branch/jump unit circuitry, floating-point unit (FPU) circuitry, etc. The control unit circuitryincludes semiconductor-based circuits structured to control (e.g., coordinate) data movement within the corresponding core. The AL circuitryincludes semiconductor-based circuits structured to perform one or more mathematic and/or logic operations on the data within the corresponding core. The AL circuitryof some examples performs integer based operations. In other examples, the AL circuitryalso performs floating point operations. In yet other examples, the AL circuitrymay include first AL circuitry that performs integer based operations and second AL circuitry that performs floating point operations. In some examples, the AL circuitrymay be referred to as an Arithmetic Logic Unit (ALU). The registersare semiconductor-based structures to store data and/or instructions such as results of one or more of the operations performed by the AL circuitryof the corresponding core. For example, the registersmay include vector register(s), SIMD register(s), general purpose register(s), flag register(s), segment register(s), machine specific register(s), instruction pointer register(s), control register(s), debug register(s), memory management register(s), machine check register(s), etc. The registersmay be arranged in a bank as shown in. Alternatively, the registersmay be organized in any other arrangement, format, or structure including distributed throughout the coreto shorten access time. The second busmay implement at least one of an I2C bus, a SPI bus, a PCI bus, or a PCIe bus.

802 800 800 Each coreand/or, more generally, the microprocessormay include additional and/or alternate structures to those shown and described above. For example, one or more clock circuits, one or more power supplies, one or more power gates, one or more cache home agents (CHAs), one or more converged/common mesh stops (CMSs), one or more shifters (e.g., barrel shifter(s)) and/or other circuitry may be present. The microprocessoris a semiconductor device fabricated to include many transistors interconnected to implement the structures described above in one or more integrated circuits (ICs) contained in one or more packages. The processor circuitry may include and/or cooperate with one or more accelerators. In some examples, accelerators are implemented by logic circuitry to perform certain tasks more quickly and/or efficiently than can be done by a general purpose processor. Examples of accelerators include ASICs and FPGAs such as those discussed herein. A GPU or other programmable device can also be an accelerator. Accelerators may be on-board the processor circuitry, in the same chip package as the processor circuitry and/or in one or more separate packages from the processor circuitry.

9 FIG. 7 FIG. 8 FIG. 712 700 900 900 800 900 is a block diagram of another example implementation of the processor circuitryof. In this example, the processor circuitryis implemented by FPGA circuitry. The FPGA circuitrycan be used, for example, to perform operations that could otherwise be performed by the example microprocessorofexecuting corresponding machine readable instructions. However, once configured, the FPGA circuitryinstantiates the machine readable instructions in hardware and, thus, can often execute the operations faster than they could be performed by a general purpose microprocessor executing the corresponding software.

800 900 900 900 900 900 8 FIG. 3 6 FIG.- 9 FIG. 3 6 FIGS.- 3 6 FIG.- 3 6 FIGS.- 3 6 FIGS.- More specifically, in contrast to the microprocessorofdescribed above (which is a general purpose device that may be programmed to execute some or all of the machine readable instructions represented by the flowcharts ofbut whose interconnections and logic circuitry are fixed once fabricated), the FPGA circuitryof the example ofincludes interconnections and logic circuitry that may be configured and/or interconnected in different ways after fabrication to instantiate, for example, some or all of the machine readable instructions represented by the flowcharts of. In particular, the FPGAmay be thought of as an array of logic gates, interconnections, and switches. The switches can be programmed to change how the logic gates are interconnected by the interconnections, effectively forming one or more dedicated logic circuits (unless and until the FPGA circuitryis reprogrammed). The configured logic circuits enable the logic gates to cooperate in different ways to perform different operations on data received by input circuitry. Those operations may correspond to some or all of the software represented by the flowcharts of. As such, the FPGA circuitrymay be structured to effectively instantiate some or all of the machine readable instructions of the flowcharts ofas dedicated logic circuits to perform the operations corresponding to those software instructions in a dedicated manner analogous to an ASIC. Therefore, the FPGA circuitrymay perform the operations corresponding to the some or all of the machine readable instructions offaster than the general purpose microprocessor can execute the same.

9 FIG. 9 FIG. 8 FIG. 3 6 FIGS.- 9 FIG. 900 900 902 904 906 904 900 904 906 800 900 908 910 912 908 910 908 908 908 In the example of, the FPGA circuitryis structured to be programmed (and/or reprogrammed one or more times) by an end user by a hardware description language (HDL) such as Verilog. The FPGA circuitryof, includes example input/output (I/O) circuitryto obtain and/or output data to/from example configuration circuitryand/or external hardware (e.g., external hardware circuitry). For example, the configuration circuitrymay implement interface circuitry that may obtain machine readable instructions to configure the FPGA circuitry, or portion(s) thereof. In some such examples, the configuration circuitrymay obtain the machine readable instructions from a user, a machine (e.g., hardware circuitry (e.g., programmed or dedicated circuitry) that may implement an Artificial Intelligence/Machine Learning (AI/ML) model to generate the instructions), etc. In some examples, the external hardwaremay implement the microprocessorof. The FPGA circuitryalso includes an array of example logic gate circuitry, a plurality of example configurable interconnections, and example storage circuitry. The logic gate circuitryand interconnectionsare configurable to instantiate one or more operations that may correspond to at least some of the machine readable instructions ofand/or other desired operations. The logic gate circuitryshown inis fabricated in groups or blocks. Each block includes semiconductor-based electrical structures that may be configured into logic circuits. In some examples, the electrical structures include logic gates (e.g., And gates, Or gates, Nor gates, etc.) that provide basic building blocks for logic circuits. Electrically controllable switches (e.g., transistors) are present within each of the logic gate circuitryto enable configuration of the electrical structures and/or the logic gates to form circuits to perform desired operations. The logic gate circuitrymay include other electrical structures such as look-up tables (LUTs), registers (e.g., flip-flops or latches), multiplexers, etc.

910 908 The interconnectionsof the illustrated example are conductive pathways, traces, vias, or the like that may include electrically controllable switches (e.g., transistors) whose state can be changed by programming (e.g., using an HDL instruction language) to activate or deactivate one or more connections between one or more of the logic gate circuitryto program desired logic circuits.

912 912 912 908 The storage circuitryof the illustrated example is structured to store result(s) of the one or more of the operations performed by corresponding logic gates. The storage circuitrymay be implemented by registers or the like. In the illustrated example, the storage circuitryis distributed amongst the logic gate circuitryto facilitate access and increase execution speed.

900 914 914 916 916 900 918 920 922 918 9 FIG. The example FPGA circuitryofalso includes example Dedicated Operations Circuitry. In this example, the Dedicated Operations Circuitryincludes special purpose circuitrythat may be invoked to implement commonly used functions to avoid the need to program those functions in the field. Examples of such special purpose circuitryinclude memory (e.g., DRAM) controller circuitry, PCIe controller circuitry, clock circuitry, transceiver circuitry, memory, and multiplier-accumulator circuitry. Other types of special purpose circuitry may be present. In some examples, the FPGA circuitrymay also include example general purpose programmable circuitrysuch as an example CPUand/or an example DSP. Other general purpose programmable circuitrymay additionally or alternatively be present such as a GPU, an XPU, etc., that can be programmed to perform other operations.

8 9 FIGS.and 7 FIG. 9 FIG. 7 FIG. 8 FIG. 9 FIG. 3 6 FIGS.- 8 FIG. 3 6 FIGS.- 9 FIG. 3 6 FIGS.- 2 FIG. 2 FIG. 712 920 712 800 900 802 900 Althoughillustrate two example implementations of the processor circuitryof, many other approaches are contemplated. For example, as mentioned above, modern FPGA circuitry may include an on-board CPU, such as one or more of the example CPUof. Therefore, the processor circuitryofmay additionally be implemented by combining the example microprocessorofand the example FPGA circuitryof. In some such hybrid examples, a first portion of the machine readable instructions represented by the flowcharts ofmay be executed by one or more of the coresof, a second portion of the machine readable instructions represented by the flowcharts ofmay be executed by the FPGA circuitryofand/or a third portion of the machine readable instructions represented by the flowcharts ofmay be executed by an ASIC. It should be understood that some or all of the circuitry ofmay, thus, be instantiated at the same or different times. Some or all of the circuitry may be instantiated, for example, in one or more threads executing concurrently and/or in series. Moreover, in some examples, some or all of the circuitry ofmay be implemented within one or more virtual machines and/or containers executing on the microprocessor.

712 800 900 712 7 FIG. 8 FIG. 9 FIG. 7 FIG. In some examples, the processor circuitryofmay be in one or more packages. For example, the processor circuitryofand/or the FPGA circuitryofmay be in one or more packages. In some examples, an XPU may be implemented by the processor circuitryof, which may be in one or more packages. For example, the XPU may include a CPU in one package, a DSP in another package, a GPU in yet another package, and an FPGA in still yet another package.

1005 732 1005 1005 1005 732 1005 732 300 400 500 600 1005 128 732 1005 300 700 732 122 1005 732 7 FIG. 10 FIG. 7 FIG. 3 6 FIGS.- 3 FIG. 2 FIG. 7 FIG. A block diagram illustrating an example software distribution platformto distribute software such as the example machine readable instructionsofto hardware devices owned and/or operated by third parties is illustrated in. The example software distribution platformmay be implemented by any computer server, data facility, cloud service, etc., capable of storing and transmitting software to other computing devices. The third parties may be customers of the entity owning and/or operating the software distribution platform. For example, the entity that owns and/or operates the software distribution platformmay be a developer, a seller, and/or a licensor of software such as the example machine readable instructionsof. The third parties may be consumers, users, retailers, OEMs, etc., who purchase and/or license the software for use and/or re-sale and/or sub-licensing. In the illustrated example, the software distribution platformincludes one or more servers and one or more storage devices. The storage devices store the machine readable instructions, which may correspond to the example machine readable instructions,,,of, as described above. The one or more servers of the example software distribution platformare in communication with a network, which may correspond to any one or more of the Internet and/or any of the example networks described above. In some examples, the one or more servers are responsive to requests to transmit the software to a requesting party as part of a commercial transaction. Payment for the delivery, sale, and/or license of the software may be handled by the one or more servers of the software distribution platform and/or by a third party payment entity. The servers enable purchasers and/or licensors to download the machine readable instructionsfrom the software distribution platform. For example, the software, which may correspond to the example machine readable instructionsof, may be downloaded to the example processor platform, which is to execute the machine readable instructionsto implement the engagement analysis circuitryof. In some examples, one or more servers of the software distribution platformperiodically offer, transmit, and/or force updates to the software (e.g., the example machine readable instructionsof) to ensure improvements, patches, updates, etc., are distributed and applied to the software at the end user devices.

From the foregoing, it will be appreciated that example systems, methods, apparatus, and articles of manufacture have been disclosed that determine audience engagement. Disclosed systems, methods, apparatus, and articles of manufacture improve the efficiency of using a computing device by determining audience engagement and determining audience engagement classifications. Disclosed systems, methods, apparatus, and articles of manufacture are accordingly directed to one or more improvement(s) in the operation of a machine such as a computer or other electronic and/or mechanical device.

Example methods, apparatus, systems, and articles of manufacture to determine audience engagement are disclosed herein.  Further examples and combinations thereof include the following:

Example 1 includes a system comprising interface circuitry, programmable circuitry, and instructions to program the programmable circuitry to obtain audio of a media presentation, obtain ambient noise in an area associated with the media presentation, determine an intensity of a difference between the audio and the ambient noise, and determine an engagement level of an audience of the media presentation based on a duration the intensity satisfies a threshold value.

Example 2 includes the system of example 1, wherein the media presentation is a television program displayed on a television, the audio is audio of the television program played through a speaker, and the programmable circuitry is to obtain the audio from a first microphone directed at the speaker, and obtain the ambient noise from a second microphone directed at the area associated with the media presentation.

Example 3 includes the system of example 1, wherein the determination of the engagement level is based on an output of a neural network classifier.

Example 4 includes the system of example 1, wherein the programmable circuitry is to determine the audience is not engaged when the intensity is greater than a threshold value.

Example 5 includes the system of example 1, wherein the programmable circuitry is to determine the audience is engaged when the intensity is less than a threshold value.

Example 6 includes the system of example 1, wherein the engagement level of the audience is inversely proportional to the intensity of the difference between the audio and the ambient noise.

Example 7 includes the system of example 1, wherein the programmable circuitry is to determine if an audience member is present based on activity of a meter device.

Example 8 includes the system of example 1, wherein the determination of the engagement level is based on a genre of the audio and at least one of an audio volume change or a channel change.

Example 9 includes a computer readable medium comprising instructions which, when executed by processor circuitry, cause the processor circuitry to obtain audio of a media presentation, obtain ambient noise in an area associated with the media presentation, determine an intensity of a difference between the audio and the ambient noise, and determine an engagement level of an audience of the media presentation based on a duration the intensity satisfies a threshold value.

Example 10 includes the computer readable storage medium of example 9, wherein the media presentation is a television program displayed on a television, the audio is audio of the television program played through a speaker, and wherein the instructions, when executed, cause processor circuitry to obtain the audio from a first microphone directed at the speaker, and obtain the ambient noise from a second microphone directed at the area associated with the media presentation.

Example 11 includes the computer readable storage medium of example 9, wherein the determination of the engagement level is based on an output of a neural network classifier.

Example 12 includes the computer readable storage medium of example 9 wherein the instructions, when executed, cause the processor circuitry to determine the audience is not engaged when the intensity is greater than a threshold value.

Example 13 includes the computer readable storage medium of example 9 wherein the instructions, when executed, cause the processor circuitry to determine the audience is engaged when the intensity is less than a threshold value.

Example 14 includes the computer readable storage medium of example 9, wherein the engagement level of the audience is inversely proportional to the intensity of the difference between the audio and the ambient noise.

Example 15 includes the computer readable storage medium of example 9, wherein the programmable circuitry is to determine if an audience member is present based on activity of a meter device.

Example 16 includes the computer readable storage medium of example 9, wherein the determination of the engagement level is based on a genre of the audio and at least one of an audio volume change or a channel change.

Example 17 includes a method comprising obtaining, by executing an instruction with processor circuitry, audio of a media presentation, obtaining, by executing an instruction with the processor circuitry, ambient noise in an area associated with the media presentation, determining, by executing an instruction with the processor circuitry, an intensity of a difference between the audio and the ambient noise, and determining, by executing an instruction with the processor circuitry, an engagement level of an audience of the media presentation based on a duration the intensity satisfies a threshold value.

Example 18 includes the method of example 17, wherein the media presentation is a television program displayed on a television, the audio is audio of the television program played through a speaker, and further including obtaining the audio from a first microphone directed at the speaker, and obtaining the ambient noise from a second microphone directed at the area associated with the media presentation.

Example 19 includes the method of example 17, wherein the determining of the engagement level is based on an output of a neural network classifier.

Example 20 includes the method of example 17, further including determining the audience is not engaged when the intensity is greater than a threshold value.

Example 21 includes the method of example 17, further including determining the audience is engaged when the intensity is less than a threshold value.

Example 22 includes the method of example 17, wherein the engagement level of the audience is inversely proportional to the intensity of the difference between the audio and the ambient noise.

Example 23 includes the method of example 17, further including determining if an audience member is present based on activity of a meter device.

Example 24 includes the method of example 17, further including determining the engagement level based on a genre of the audio and at least one of an audio volume change or a channel change.

The following claims are hereby incorporated into this Detailed Description by this reference. Although certain example systems, methods, apparatus, and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all systems, methods, apparatus, and articles of manufacture fairly falling within the scope of the claims of this patent.